Techniques for memory bandwidth optimization in bi-predicted motion vector refinement

ABSTRACT

A method and apparatus for encoding of a video sequence in an encoder or decoding of the video sequence in a decoder includes parsing an initial motion vector from the video sequence associated with a block. A plurality of samples are determined and pre-fetched to permit both motion vector refinement and motion compensation based on parsing the initial motion vector. Motion vector refinement is performed to determine a final motion vector using a first subset of the plurality of samples, and motion compensation is performed using a second subset of the plurality of samples.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims priority under 35 U.S.C. § 119 from U.S.Provisional Application No. 62/685,257 filed on Jun. 14, 2018 in theU.S. Patent & Trademark Office, the disclosure of which is incorporatedherein by reference in its entirety.

FIELD

The disclosed subject matter relates to video coding and decoding, andmore specifically, to the selection of motion compensation interpolationfilters in relation to memory bandwidth in the presence of motion vectorrefinement.

BACKGROUND

Video coding and decoding using inter-picture prediction with motioncompensation has been known for decades. Uncompressed digital video canconsist of a series of pictures, each picture having a spatial dimensionof, for example, 1920×1080 luminance samples and associated chrominancesamples. The series of pictures can have a fixed or variable picturerate (informally also known as frame rate), of, for example, 60 picturesper second or 60 Hz. Uncompressed video has significant bitraterequirements. For example, 1080p60 4:2:0 video at 8 bits per sample(1920×1080 luminance sample resolution at 60 Hz frame rate) requiresclose to 1.5 Gbit/s bandwidth. An hour of such video requires more than600 GByte of storage space.

One purpose of video coding and decoding includes the reduction ofredundancy in the input video signal, through compression. Compressioncan help reducing aforementioned bandwidth or storage spacerequirements, in some cases by two orders of magnitude or more. Bothlossless and lossy compression, as well as a combination thereof, can beemployed. Lossless compression refers to techniques where an exact copyof the original signal can be reconstructed from the compressed originalsignal. When using lossy compression, the reconstructed signal may notbe identical to the original signal, but the distortion between originaland reconstructed signal is negligible so as to render the reconstructedsignal useful for the intended application. In the case of video, lossycompression is widely employed. The amount of tolerated distortiondepends on the application; for example, users of certain consumerstreaming applications may tolerate higher distortion than users oftelevision contribution applications. The compression ratio achievablecan reflect that: higher allowable/tolerable distortion can yield highercompression ratios.

A video encoder and decoder can utilize techniques from several broadcategories, including, for example, motion compensation, transform,quantization, and entropy coding, some of which will be introducedbelow.

Motion compensation can be a lossy compression technique and can relateto techniques where a block of sample data from a previouslyreconstructed picture or part thereof (reference picture), after beingspatially shifted in a direction indicated by a motion vector (MVhenceforth), is used for the prediction of a newly reconstructed pictureor picture part. In some cases, the reference picture can be the same asthe picture currently under reconstruction. MVs can have two dimensionsX and Y, or three dimensions, the third being an indication of thereference picture in use (the latter, indirectly, can be a timedimension).

The motion vector to be used in the motion compensation can be ofsub-sample (sub-pel) accuracy. In at least such cases, motioncompensation involves interpolation of the reconstructed sample from aplurality of reference picture samples, using an interpolation filter.Such an interpolation filter can, for example, include an 8 tap (in eachdimension) filter. More generally, the use of an n-tap interpolationfilter can require the use of n samples for interpolation. Henceforth,only filtering in a single dimension is considered; a person skilled inthe art can readily generalize the one-dimensional considerationsdescribed herein to additional dimensions.

In some cases, the motion vector used in the motion compensation can becoded directly in the bitstream, or as difference information relativeto already reconstructed metadata, such as the motion vector data ofblocks of the picture under reconstruction. In other cases, however,that motion vector can itself be the result of decoder-siteinterpolation. A well-known technique for such decoder-site motionvector derivation is known in the case of bi-predicted blocks, where themotion vector to be used for motion compensation can be interpolatedfrom the motion vectors used in the two reference blocks.

Yet other techniques can require the use of sample data (in contrast tometadata) belonging to the picture under reconstruction in the creationof a motion vector for the use to motion compensate a block. Forexample, one such technique is described in JVET-D0029, entitled“Decoder-Site Motion Vector Refinement Based on Bilateral TemplateMatching” available fromhttp://phenix.it-sudparis.eu/jvet/doc_end_user/current_document.php?id=2725.The technique described therein can be used in the context ofbi-prediction (prediction from two reference pictures). Motioncompensation according to this exemplary technique involves the creationof a template block using traditional bi-predictive reconstructiontechnique. That template can be used for a decoder-side motion “search”mechanism, out of which refinement motion vectors can be generated,which, in turn are the input for the motion compensation step. Accordingto JVET-D0029, such technique can have significant positive impact onthe compression performance of a codec.

SUMMARY

Disclosed herein are techniques for improving memory access bandwidth ina video encoder/decoder that uses decoder-side motion vector refinement.According to some embodiments herein, only a well-defined number, thatcan be zero, of samples need to be pre-fetched when using motion vectorrefinement, and such pre-fetch can occur in a single pipeline step.

According to an aspect of the disclosure, a method for encoding of avideo sequence in an encoder or decoding of the video sequence in adecoder includes parsing an initial motion vector from the videosequence associated with a block; determining a plurality of samples topermit both motion vector refinement and motion compensation based onparsing the initial motion vector; pre-fetching the plurality ofsamples; performing the motion vector refinement to determine a finalmotion vector using a first subset of the plurality of samples; andperforming the motion compensation using a second subset of theplurality of samples.

According to an aspect of the disclosure, a device for encoding of avideo sequence in an encoder or decoding of the video sequence in adecoder includes at least one memory configured to store program code;and at least one processor configured to read the program code andoperate as instructed by the program code, the program code including:parsing code configured to cause the at least one processor to parse aninitial motion vector from the video sequence associated with a block;determining code configured to cause the at least one processor todetermine a plurality of samples to permit both motion vector refinementand motion compensation based on parsing the initial motion vector;pre-fetching code to pre-fetch the plurality of samples; firstperforming code configured to cause the at least one processor toperform the motion vector refinement to determine a final motion vectorusing a first subset of the plurality of samples; and second performingcode to perform the motion compensation using a second subset of theplurality of samples.

According to an aspect of the disclosure, a non-transitorycomputer-readable medium storing instructions, the instructionscomprising: one or more instructions that, when executed by one or moreprocessors of a device, cause the one or more processors to: parse aninitial motion vector from the video sequence associated with a block;determine a plurality of samples to permit both motion vector refinementand motion compensation based on parsing the initial motion vector;pre-fetch the plurality of samples; perform the motion vector refinementto determine a final motion vector using a first subset of the pluralityof samples; and perform the motion compensation using a second subset ofthe plurality of samples.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1 is a schematic illustration of a simplified block diagram of acommunication system in accordance with an embodiment.

FIG. 2 is a schematic illustration of a simplified block diagram of astreaming system in accordance with an embodiment.

FIG. 3 is a schematic illustration of a simplified block diagram of adecoder in accordance with an embodiment.

FIG. 4 is a schematic illustration of a simplified block diagram of anencoder in accordance with an embodiment.

FIG. 5 is a schematic illustration of a flow chart of motioncompensation with motion vector refinement in accordance with anembodiment.

FIG. 6 is a schematic illustration of samples required for motioninterpolation in accordance with an embodiment.

FIG. 7 is a schematic illustration of samples required for motioninterpolation with motion vector refinement in accordance with anembodiment.

FIG. 8 is a schematic illustration of samples lines required for motioninterpolation with motion vector refinement in accordance with anembodiment.

FIG. 9 is a flowchart of an example process in accordance with anembodiment.

FIG. 10 is a schematic illustration of a computer system in accordancewith an embodiment.

PROBLEM TO BE SOLVED

Techniques such as the one described in JVET-D0029 can have asignificant impact on the memory bandwidth requirements of a decoder.Specifically, the sample data required for the refinement step (templategeneration) may be different from the sample data used forreconstruction, requiring the decoder to access, for the reconstructionof a given block, more sample data than what would be needed if onlytraditional bi-prediction were in use. Using one or more techniques, theadditional memory bandwidth, if any, needs to be determinable, andminimized in relation to the coding gain observed based on theminimization-imposed constraints.

DETAILED DESCRIPTION

FIG. 1 illustrates a simplified block diagram of a communication system(100) according to an embodiment of the present disclosure. The system(100) may include at least two terminals (110-120) interconnected via anetwork (150). For unidirectional transmission of data, a first terminal(110) may code video data at a local location for transmission to theother terminal (120) via the network (150). The second terminal (120)may receive the coded video data of the other terminal from the network(150), decode the coded data and display the recovered video data.Unidirectional data transmission may be common in media servingapplications and the like.

FIG. 1 illustrates a second pair of terminals (130, 140) provided tosupport bidirectional transmission of coded video that may occur, forexample, during videoconferencing. For bidirectional transmission ofdata, each terminal (130, 140) may code video data captured at a locallocation for transmission to the other terminal via the network (150).Each terminal (130, 140) also may receive the coded video datatransmitted by the other terminal, may decode the coded data and maydisplay the recovered video data at a local display device.

In FIG. 1, the terminals (110-140) may be illustrated as servers,personal computers and smart phones but the principles of the presentdisclosure may be not so limited. Embodiments of the present disclosurefind application with laptop computers, tablet computers, media playersand/or dedicated video conferencing equipment. The network (150)represents any number of networks that convey coded video data among theterminals (110-140), including for example wireline and/or wirelesscommunication networks. The communication network (150) may exchangedata in circuit-switched and/or packet-switched channels. Representativenetworks include telecommunications networks, local area networks, widearea networks and/or the Internet. For the purposes of the presentdiscussion, the architecture and topology of the network (150) may beimmaterial to the operation of the present disclosure unless explainedherein below.

FIG. 2 illustrates, as an example for an application for the disclosedsubject matter, the placement of a video encoder and decoder in astreaming environment. The disclosed subject matter can be equallyapplicable to other video enabled applications, including, for example,video conferencing, digital TV, storing of compressed video on digitalmedia including CD, DVD, memory stick and the like, and so on.

A streaming system may include a capture subsystem (213), that caninclude a video source (201), for example a digital camera, creating afor example uncompressed video sample stream (202). That sample stream(202), depicted as a bold line to emphasize a high data volume whencompared to encoded video bitstreams, can be processed by an encoder(203) coupled to the camera (201). The encoder (203) can includehardware, software, or a combination thereof to enable or implementaspects of the disclosed subject matter as described in more detailbelow. The encoded video bitstream (204), depicted as a thin line toemphasize the lower data volume when compared to the sample stream, canbe stored on a streaming server (205) for future use. One or morestreaming clients (206, 208) can access the streaming server (205) toretrieve copies (207, 209) of the encoded video bitstream (204). Aclient (206) can include a video decoder (210) which decodes theincoming copy of the encoded video bitstream (207) and creates anoutgoing video sample stream (211) that can be rendered on a display(212) or other rendering device (not depicted). In some streamingsystems, the video bitstreams (204, 207, 209) can be encoded accordingto certain video coding/compression standards. Examples of thosestandards include ITU-T Recommendation H.265. Under development is avideo coding standard informally known as Versatile Video Coding or VVC.The disclosed subject matter may be used in the context of VVC.

FIG. 3 may be a functional block diagram of a video decoder (210)according to an embodiment of the present invention.

A receiver (310) may receive one or more codec video sequences to bedecoded by the decoder (210); in the same or another embodiment, onecoded video sequence at a time, where the decoding of each coded videosequence is independent from other coded video sequences. The codedvideo sequence may be received from a channel (312), which may be ahardware/software link to a storage device which stores the encodedvideo data. The receiver (310) may receive the encoded video data withother data, for example, coded audio data and/or ancillary data streams,that may be forwarded to their respective using entities (not depicted).The receiver (310) may separate the coded video sequence from the otherdata. To combat network jitter, a buffer memory (315) may be coupled inbetween receiver (310) and entropy decoder/parser (320) (“parser”henceforth). When receiver (310) is receiving data from a store/forwarddevice of sufficient bandwidth and controllability, or from anisosychronous network, the buffer (315) may not be needed, or can besmall. For use on best effort packet networks such as the Internet, thebuffer (315) may be required, can be comparatively large and canadvantageously be of adaptive size.

The video decoder (210) may include a parser (320) to reconstructsymbols (321) from the entropy coded video sequence. Categories of thosesymbols include information used to manage operation of the decoder(210), and potentially information to control a rendering device such asa display (212) that is not an integral part of the decoder but can becoupled to it, as was shown in FIG. 2. The control information for therendering device(s) may be in the form of Supplementary EnhancementInformation (SEI) messages or Video Usability Information (VUI)parameter set fragments (not depicted). The parser (320) mayparse/entropy-decode the received coded video sequence. The coding ofthe coded video sequence can be in accordance with a video codingtechnology or standard, and can follow principles well known to a personskilled in the art, including variable length coding, Huffman coding,arithmetic coding with or without context sensitivity, and so forth. Theparser (320) may extract from the coded video sequence, a set ofsubgroup parameters for at least one of the subgroups of pixels in thevideo decoder, based upon at least one parameters corresponding to thegroup. Subgroups can include Groups of Pictures (GOPs), pictures, tiles,slices, macroblocks, Coding Units (CUs), blocks, Transform Units (TUs),Prediction Units (PUs) and so forth. The entropy decoder/parser may alsoextract from the coded video sequence information such as transformcoefficients, quantizer parameter values, motion vectors, and so forth.

The parser (320) may perform entropy decoding/parsing operation on thevideo sequence received from the buffer (315), so to create symbols(321).

Reconstruction of the symbols (321) can involve multiple different unitsdepending on the type of the coded video picture or parts thereof (suchas: inter and intra picture, inter and intra block), and other factors.Which units are involved, and how, can be controlled by the subgroupcontrol information that was parsed from the coded video sequence by theparser (320). The flow of such subgroup control information between theparser (320) and the multiple units below is not depicted for clarity.

Beyond the functional blocks already mentioned, decoder 210 can beconceptually subdivided into a number of functional units as describedbelow. In a practical implementation operating under commercialconstraints, many of these units interact closely with each other andcan, at least partly, be integrated into each other. However, for thepurpose of describing the disclosed subject matter, the conceptualsubdivision into the functional units below is appropriate.

A first unit is the scaler/inverse transform unit (351). Thescaler/inverse transform unit (351) receives quantized transformcoefficient as well as control information, including which transform touse, block size, quantization factor, quantization scaling matrices,etc. as symbol(s) (321) from the parser (320). It can output blockscomprising sample values, that can be input into aggregator (355).

In some cases, the output samples of the scaler/inverse transform (351)can pertain to an intra coded block; that is: a block that is not usingpredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit (352). In some cases, the intra pictureprediction unit (352) generates a block of the same size and shape ofthe block under reconstruction, using surrounding already reconstructedinformation fetched from the current (partly reconstructed) picture(356). The aggregator (355), in some cases, adds, on a per sample basis,the prediction information the intra prediction unit (352) has generatedto the output sample information as provided by the scaler/inversetransform unit (351).

In other cases, the output samples of the scaler/inverse transform unit(351) can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a Motion Compensation Prediction unit (353) canaccess reference picture memory (357) to fetch samples used forprediction. After motion compensating the fetched samples in accordancewith the symbols (321) pertaining to the block, these samples can beadded by the aggregator (355) to the output of the scaler/inversetransform unit (in this case called the residual samples or residualsignal) so to generate output sample information. The addresses withinthe reference picture memory form where the motion compensation unitfetches prediction samples can be controlled by motion vectors,available to the motion compensation unit in the form of symbols (321)that can have, for example X, Y, and reference picture components.Motion compensation also can include interpolation of sample values asfetched from the reference picture memory when sub-sample exact motionvectors are in use, motion vector prediction mechanisms, and so forth.

The output samples of the aggregator (355) can be subject to variousloop filtering techniques in the loop filter unit (356). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video bitstream andmade available to the loop filter unit (356) as symbols (321) from theparser (320), but can also be responsive to meta-information obtainedduring the decoding of previous (in decoding order) parts of the codedpicture or coded video sequence, as well as responsive to previouslyreconstructed and loop-filtered sample values.

The output of the loop filter unit (356) can be a sample stream that canbe output to the render device (212) as well as stored in the referencepicture memory (356) for use in future inter-picture prediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future prediction. Once a coded picture is fullyreconstructed and the coded picture has been identified as a referencepicture (by, for example, parser (320)), the current reference picture(356) can become part of the reference picture buffer (357), and a freshcurrent picture memory can be reallocated before commencing thereconstruction of the following coded picture.

The video decoder 320 may perform decoding operations according to apredetermined video compression technology that may be documented in astandard, such as ITU-T Rec. H.265. The coded video sequence may conformto a syntax specified by the video compression technology or standardbeing used, in the sense that it adheres to the syntax of the videocompression technology or standard, as specified in the videocompression technology document or standard and specifically in theprofiles document therein. Also necessary for compliance can be that thecomplexity of the coded video sequence is within bounds as defined bythe level of the video compression technology or standard. In somecases, levels restrict the maximum picture size, maximum frame rate,maximum reconstruction sample rate (measured in, for example megasamplesper second), maximum reference picture size, and so on. Limits set bylevels can, in some cases, be further restricted through HypotheticalReference Decoder (HRD) specifications and metadata for HRD buffermanagement signaled in the coded video sequence.

In an embodiment, the receiver (310) may receive additional (redundant)data with the encoded video data. The additional data may be included aspart of the coded video sequence(s). The additional data may be used bythe video decoder (320) to properly decode the data and/or to moreaccurately reconstruct the original video data. Additional data can bein the form of, for example, temporal, spatial, or SNR enhancementlayers, redundant slices, redundant pictures, forward error correctioncodes, and so on.

FIG. 4 may be a functional block diagram of a video encoder (203)according to an embodiment of the present disclosure.

The encoder (203) may receive video samples from a video source (201)(that is not part of the encoder) that may capture video image(s) to becoded by the encoder (203).

The video source (201) may provide the source video sequence to be codedby the encoder (203) in the form of a digital video sample stream thatcan be of any suitable bit depth (for example: 8 bit, 10 bit, 12 bit, .. . ), any colorspace (for example, BT.601 Y CrCB, RGB, . . . ) and anysuitable sampling structure (for example Y CrCb 4:2:0, Y CrCb 4:4:4). Ina media serving system, the video source (201) may be a storage devicestoring previously prepared video. In a videoconferencing system, thevideo source (203) may be a camera that captures local image informationas a video sequence. Video data may be provided as a plurality ofindividual pictures that impart motion when viewed in sequence. Thepictures themselves may be organized as a spatial array of pixels,wherein each pixel can comprise one or more sample depending on thesampling structure, color space, etc. in use. A person skilled in theart can readily understand the relationship between pixels and samples.The description below focuses on samples.

According to an embodiment, the encoder (203) may code and compress thepictures of the source video sequence into a coded video sequence (443)in real time or under any other time constraints as required by theapplication. Enforcing appropriate coding speed is one function ofController (450). Controller (450) controls other functional units asdescribed below and is functionally coupled to these units. The couplingis not depicted for clarity. Parameters set by controller (450) caninclude rate control related parameters (picture skip, quantizer, lambdavalue of rate-distortion optimization techniques, . . . ), picture size,group of pictures (GOP) layout, maximum motion vector search range, andso forth. A person skilled in the art can readily identify otherfunctions of controller (450) as they may pertain to video encoder (203)optimized for a certain system design.

Some video encoders operate in what a person skilled in the are readilyrecognizes as a “coding loop”. As an oversimplified description, acoding loop can consist of the encoding part of an encoder (430)(“source coder” henceforth) (responsible for creating symbols based onan input picture to be coded, and a reference picture(s)), and a (local)decoder (433) embedded in the encoder (203) that reconstructs thesymbols to create the sample data that a (remote) decoder also wouldcreate (as any compression between symbols and coded video bitstream islossless in the video compression technologies considered in thedisclosed subject matter). That reconstructed sample stream is input tothe reference picture memory (434). As the decoding of a symbol streamleads to bit-exact results independent of decoder location (local orremote), the reference picture buffer content is also bit exact betweenlocal encoder and remote encoder. In other words, the prediction part ofan encoder “sees” as reference picture samples exactly the same samplevalues as a decoder would “see” when using prediction during decoding.This fundamental principle of reference picture synchronicity (andresulting drift, if synchronicity cannot be maintained, for examplebecause of channel errors) is well known to a person skilled in the art.

The operation of the “local” decoder (433) can be the same as of a“remote” decoder (210), which has already been described in detail abovein conjunction with FIG. 3. Briefly referring also to FIG. 3, however,as symbols are available and en/decoding of symbols to a coded videosequence by entropy coder (445) and parser (320) can be lossless, theentropy decoding parts of decoder (210), including channel (312),receiver (310), buffer (315), and parser (320) may not be fullyimplemented in local decoder (433).

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that is present in adecoder also necessarily needs to be present, in substantially identicalfunctional form, in a corresponding encoder. For this reason, thedisclosed subject matter focusses on decoder operation. The descriptionof encoder technologies can be abbreviated as they are the inverse ofthe comprehensively described decoder technologies. Only in certainareas a more detail description is required and provided below.

As part of its operation, the source coder (430) may perform motioncompensated predictive coding, which codes an input frame predictivelywith reference to one or more previously-coded frames from the videosequence that were designated as “reference frames.” In this manner, thecoding engine (432) codes differences between pixel blocks of an inputframe and pixel blocks of reference frame(s) that may be selected asprediction reference(s) to the input frame.

The local video decoder (433) may decode coded video data of frames thatmay be designated as reference frames, based on symbols created by thesource coder (430). Operations of the coding engine (432) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 4), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (433) replicates decodingprocesses that may be performed by the video decoder on reference framesand may cause reconstructed reference frames to be stored in thereference picture cache (434). In this manner, the encoder (203) maystore copies of reconstructed reference frames locally that have commoncontent as the reconstructed reference frames that will be obtained by afar-end video decoder (absent transmission errors).

The predictor (435) may perform prediction searches for the codingengine (432). That is, for a new frame to be coded, the predictor (435)may search the reference picture memory (434) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(435) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (435), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (434).

The controller (450) may manage coding operations of the video coder(430), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (445). The entropy coder translatesthe symbols as generated by the various functional units into a codedvideo sequence, by loss-less compressing the symbols according totechnologies known to a person skilled in the art as, for exampleHuffman coding, variable length coding, arithmetic coding, and so forth.

The transmitter (440) may buffer the coded video sequence(s) as createdby the entropy coder (445) to prepare it for transmission via acommunication channel (460), which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter(440) may merge coded video data from the video coder (430) with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller (450) may manage operation of the encoder (203). Duringcoding, the controller (450) may assign to each coded picture a certaincoded picture type, which may affect the coding techniques that may beapplied to the respective picture. For example, pictures often may beassigned as one of the following frame types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other frame in the sequence as a source of prediction.Some video codecs allow for different types of Intra pictures,including, for example Independent Decoder Refresh Pictures. A personskilled in the art is aware of those variants of I pictures and theirrespective applications and features.

A Predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A Bi-directionally Predictive Picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16 sampleseach) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded non-predictively,via spatial prediction or via temporal prediction with reference to onepreviously coded reference pictures. Blocks of B pictures may be codednon-predictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures.

The video coder (203) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video coder (203) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data, therefore, may conform to a syntax specified bythe video coding technology or standard being used.

In an embodiment, the transmitter (440) may transmit additional datawith the encoded video. The video coder (430) may include such data aspart of the coded video sequence. Additional data may comprisetemporal/spatial/SNR enhancement layers, other forms of redundant datasuch as redundant pictures and slices, Supplementary EnhancementInformation (SEI) messages, Visual Usability Information (VUI) parameterset fragments, and so on.

The disclosed subject matter can be applicable for motion vectorrefinement or any other technique wherein sample data from the alreadyreconstructed picture is used to influence the reconstructed of sampledata of the same given picture.

FIG. 5 shows a conceptual flow diagram of the motion compensation of ablock using a motion vector refinement technique based on sample data,as, for example, described in JVET-D0029. The technique is describedhenceforth under the assumption of two reference pictures andbi-prediction; however, it can equally apply to other forms ofprediction including, for example, multi-hypothesis prediction, mixturesof intra block copy techniques with traditional reference picture basedmotion compensation, and so forth.

In a parsing step (501), one or more initial motion vector(s) aregenerated, by, for example, parsing the bitstream and decoding includedsymbols related to the motion vector(s), and using those decoded symbolsin conjunction with already available (reconstructed) metadata (such asthe motion vectors of surrounding blocks). While such a technique iscommonly known as “parsing”, it can, as described above, includemechanisms that go well beyond a strict definition of parsing (in thesense of converting a bitstream into a symbol stream). The result of theparsing step (501) are one or more initial motion vector(s) (“iMV(s)”).

In a first pre-fetch step (502), reference picture memory can beaccessed to obtain the sample data that can be required for thegeneration of the final motion vectors (“fMV(s)”) through motion vectorrefinement. The number of such required memory access is describedbelow. With only a few exceptions, encoder and decoder systems store thereference picture samples in reference picture memory. Such referencepicture memory can be relatively slow and its access can be governed bycertain hardware constraints. With only a few exceptions, a pre-fetchstep can access reference picture memory in granularities such as cachelines, and copy entire cache lines into fast memory, cache memory,registers, or the like (“fast memory” henceforth), for quick accessduring the,in some cases computationally expensive, refinement step. Thelocation of the sample data in the reference picture memory that isrequired for the generation of the fMVs) can be determined bytraditional motion compensation techniques based on the iMVs.

In the refinement step (503), the pre-fetched reference picture sampledata of step (502), in conjunction with the iMVs, and possibly otherdata, are used to create the fMVs. The disclosed subject matter does notlimit the characteristics of the refinement step in any way. Onepossible refinement step can be as described in JVET-D0029.

In a second pre-fetch step, sample data in the reference picture memoryas identified by the fMVs can be copied into the fast memory. Note thatin at least some cases, the sample data access in accordance of the fMVscan be different than the sample data accessed in accordance to theiMVs. (If such data were always identical, then iMV would be alwaysequal to fMV, and the refinement step would be redundant.)

Finally, a reconstruction step (505) reconstructs the samples of theblock in accordance with the fMVs. That reconstruction step can usetraditional techniques for bi-predictively coded, motion compensatedblocks.

A person skilled in the art can readily understand that both motionvector refinement (503) and reconstruction (505) can includeinterpolation filters. The filters used in those steps can be the sameor different, both in terms of memory access/bandwidth relatedproperties (such as: number of taps), and other properties (such as:adaptivity, filter coefficients in use, and so forth). The descriptionbelow assumes, for the sake of brevity, the use of the sameinterpolation filter in both refinement (503) and reconstruction (505).However, nothing herein prevents the use of interpolation filters ofdifferent characteristics, be they memory access/bandwidth related orotherwise, for refinement and reconstruction. A person skilled in theart can readily understand how the use of different filters influencesthe number of accesses required. The description below includes a fewremarks regarding that.

Referring now to FIG. 6, the memory bandwidth to reference picturememory needed for each pre-fetch step can be the number of samples inthe reference picture memory that needs to be accessed in each pre-fetchstep

The amount of samples that needs to be pre-fetched in steps (502) and(504) can be dependent on a number of factors, including:

-   -   the size of the block; and    -   the number of taps of the motion compensation interpolation        filters.

In some modern video codecs, block sizes can vary widely. Focusing thediscussion on a single dimension (“block length” henceforth), a blocklength can be as short as 4 luma samples or 2 chroma samples, and aslong as 128 samples, 256 samples, or more.

Some embodiments herein are applicable to techniques that use eight tapfilters, such as in accordance with the JVET project. Accordingly, foreach sample to be interpolated, eight reference samples need to beaccessed.

In a first example, assume a block (601) of 4 samples (only a singleline of samples is depicted). For a block length of 4, this results inthe need to access (4+8)−1=11 reference samples (shown as circles 602),assuming that samples that were recently accessed to interpolate anearlier sample in the same block stay in fast memory for the processingof later samples of the same block. Eight lines (603) are indicative ofthe eight shaded samples (605) required for interpolating a given sample(604) of the block (601).

For a block length of 16 samples (606), there is a need to access(16+8)−1=23 reference samples (607). From this example, a person skilledin the art can readily observe that the relative overhead of sampleaccess due to interpolation filters decreases with increasing blocksize. That is the case when the interpolation filter size (in taps) isindependent of the block size.

This observation can lead to certain design choices that can keep theoverhead of small block interpolation in reasonable bounds. According toan embodiment, the number of accesses to samples or lines of samples (asdescribed in more detail below), can be made dependent on the blocksize. In the same or another embodiment, for certain, pre-determinedsmaller block sizes (such as, for example, 4 samples, 8 samples, etc.),a video coding technology or standard can prohibit the use of motionvector refinement. In the same or another embodiment, for certain,pre-determined smaller block sizes, a video coding technology orstandard can mandate the use of different interpolation filters fordifferent block sizes; in order to minimize the overhead describedabove, advantageously, the interpolation filter used for smaller blocksizes can use fewer taps than interpolation filters used for largerblock sizes.

As there are two pre-fetch steps, and assuming the number of taps of theinterpolation filters used in refinement and reconstruction is the same,the number of accesses needs to be doubled. Again under the assumptionof an 8 tap interpolation filter, and focusing on a single dimension,for a four sample block, required would be 2*(4+8−1)=22 accesses toreference samples, and for a 16 sample block required would be2*(16+8−1)=46 accesses to reference samples. If the filters weredifferent, a person skilled in the art can readily modify the abovecalculation based on the number of filter taps used in each of thedifferent filters.

Assuming the iMVs and the fMVs are not too diverse, there can be anoverlap in the samples that are being fetched in the first and secondpre-fetch steps. Specifically, if the difference between iMV and fMV issmaller than the block size, there is always an overlap. The differencebetween iMV and fMV, can be a pre-determined constraint of the videocoding technology or standard. Working under the assumption that thefast memory is large enough to keep the samples of the first pre-fetchstep and the samples of the second pre-fetch steps simultaneously (or,in other words, that there is no need to flush the fast memory beforethe second pre-fetch step), it can easily be seen that, again assuming asuitably constrained maximum difference between iMV and fMV, the secondpre-fetch step does not need to fetch as many samples as the abovecalculation would suggest, because of the overlap between the sampledata addressed by the iMVs and fMVs.

In order to get to a better approximation of memory bandwidth than justnumber of samples to be copied in each pre-fetch step, therefore, thereis a third factor:

-   -   the maximum difference between the iMVs and fMVs.

Referring now to FIG. 7, and again focusing only on the one-dimensionalcase, assume a maximum displacement of 2 samples as shown by thehorizontal shift by two samples from the samples shifted according to aniMV (701), and the samples shifted according to the fMV (702). In thatcase, a majority of the pre-fetched samples of the first pre-fetch step,namely all reference samples depicted as unshaded circles (703) can bereused and do not need to be pre-fetched again in the second pre-fetchstep. However, two additional samples (704) are required in the secondpre-fetch step. For a block length of 4, an 8 tap filter, and a maximumdifference between iMV and fMV of 2, the number of accesses would be(4+8−1)+2=13, wherein the second pre-fetch step, at most, would need topre-fetch 2 samples. For a 16 sample block, the similar calculationwould be (16+8−1)+2=25.

From above examples, it should be deduced that the number of samplesthat need to be accessed is:

min((block length+filter taps+max-displacement−1), (2*(blocklength+filter taps−1))

Briefly referring to FIG. 5, in some system designs, the setup of amemory access can be considerably more expensive (in terms of time) thanthe actual memory transfer itself. Accordingly, in such systems it isadvantageous to pre-fetch all samples required for both the refinement(503) and the motion compensation/reconstruction (505) in the single(first pre-fetch (502), and omit step (504) entirely. This can bepossible when certain constraints can be imposed on the influencingfactors of block length, filter taps, overlap, as described below. Theconstraints can be imposed, for example, by a video compressiontechnology or standard.

Up to this point, considered were only the memory accesses required tomotion compensate a single block. A picture can be made up of manyblocks; with a given block's size proportionally more when the blocksize is small compared to when the block size is large. As shown in theabove examples, smaller block sizes incur substantially more overhead inmemory accesses relative to the block size than larger block sizes, andas such, the memory bandwidth requirements can increase when smallblocks are selected by the encoder.

It is well understood in video compression that a longer interpolationfilter, especially when being content adaptive, can give bettercompression performance. Similarly, more freedom in the selection ofmotion vectors, including for example freedom of the encoder inselecting differences between iMV and fMV (minimizing overlap bymaximizing the possible displacement), can give better compressionperformance. Finally, freedom of the choice of block size (including theuse of small blocks) also can increase compression performance.

Accordingly, all three influencing factors can be constrained by a videocompression technology or standard to balance their compressionperformance potential with their memory bandwidth increase potential.

So far, the description has focused on an analysis of a motion vector inonly a single dimension. A person skilled in the art can readilygeneralize the above embodiments to two dimensions and would arrive, insome cases, in approximately a power of two increase in the additionalmemory bandwidth requirements compared to what is described above.

However, such generalization may not be always needed. Specifically, inat least some encoder and decoder systems, the reference memory isaccessed not in the granularity of samples (or abstract cache lines of asize not directly related to video content properties), but in thegranularity of line buffers. A line buffer can comprise all the samples(and stored reference picture metadata, if any) of a given line ofsamples in a reference picture, reference tile, and the like. In a linebuffer based architecture, the overhead for motion refinement techniquessuch as the ones assumed above can be calculated in the granularity ofadditional line buffer fetches, using the vertical dimension only.

In an embodiment, an encoder or decoder compliant with a video codingtechnology or standard can balance a technical requirement for maximummemory bandwidth increase through the use of motion vector refinementwith the coding gain obtainable through motion vector refinement, byimposing constraints on one or more of a maximum distance between aninitial motion vector iMV and a final motion vector fMV, and a number oftaps in an interpolation filter.

In the same or another embodiment, the constraints imposed on themaximum distance between an initial motion vector iMV and a final motionvector fMV, and the number of taps in an interpolation filter, can besuch that the memory bandwidth increase through motion vector refinementcan be zero.

Referring now to FIG. 8, assume a line buffer based architecture.Accordingly, depicted henceforth is only a vertical dimension of samplesunder reconstruction or used for interpolation or motion vectorrefinement, with the understanding that those many of those samples canbe in the respective line buffers (shown only for one line of samples,and only partially).

Depicted is a block size of 4 vertical samples (801) already correctedby iMV, but the considerations below are applicable to any block size.Assume further the maximum difference between iMV and fMV is constrainedto 2 samples by the video compression technology or standard; one samplein an “up” direction is equal to one sample in a “down” direction. Thisresults, depending on fMV, in up to six samples (802) (more precisely,sample lines) that may be involved in the motion compensation of theblock. Further, consider the interpolation filter size to be constrainedto 6 samples. As a result, the number of samples (or, more precisely,sample lines) that need to be pre-fetched (803), and hence also thememory bandwidth requirements are identical to a scenario where there isan 8 tap interpolation filter and no motion vector refinement (804).Note that the six tap filter used to interpolate the six samples (802)can access up to two samples on “top” of the boundary of the six samples(802), and three samples at the bottom (marked by bold lines 805),whereas in case of the 8 tap filter, the possible access is threesamples at the top and four samples at the bottom (marked by bold lines806)

Generalizing the above observation, in the same or another embodiment,the constraints can be that the sum of the maximum distance between aninitial motion vector iMV and a final motion vector fMV, and the numberof taps in an interpolation filter used when motion vector refinement isin use, can be the same as the number of taps of an interpolation filterused when motion vector refinement is not in use. In that case, there isno increase in memory bandwidth through the use of motion vectorrefinement.

In the same or another embodiment, a certain, well-defined increase inmemory access requirements (measured, for example, in line bufferaccesses) can be accepted by a video compression technology or standard.This can be expressed by the number of taps of the interpolation filterused in conjunction with motion vector refinement (“refine-taps”), thenumber of taps of the interpolation filter taps used when no motionvector refinement is in use (“no-refine-taps”), and the maximum distancebetween an initial motion vector iMV and a final motion vector fMV(“distance”). The number of additional line buffer accesses can be(refine-taps+distance)−no-refine-taps). For example, let no-refine-tapsbe 8. If two additional line buffers are acceptable, then then videocompression technology or standard could have constraints such asrefine-taps=8 and distance=2. This example can have the advantage thatthe interpolation filter can be the same for reconstruction with orwithout motion vector refinement. A maximum distance of 2 can besufficient to obtain most of the theoretical coding efficiency gainpossible with larger values of distance, at least for some content andsome frequently used resolutions.

FIG. 9 is a flowchart of an example process 900 for encoding of a videosequence in an encoder or decoding of the video sequence in a decoder.In some implementations, one or more process blocks of FIG. 9 may beperformed by decoder 210. In some implementations, one or more processblocks of FIG. 9 may be performed by another device or a group ofdevices separate from or including decoder 210, such as encoder 203.

As shown in FIG. 9, process 900 may include parsing an initial motionvector from the video sequence associated with a block (block 901).

As further shown in FIG. 9, process 900 may include determining aplurality of samples to permit both motion vector refinement and motioncompensation based on parsing the initial motion vector (block 902).

As further shown in FIG. 9, process 900 may include pre-fetching theplurality of samples (block 903).

As further shown in FIG. 9, process 900 may include performing themotion vector refinement to determine a final motion vector using afirst subset of the plurality of samples (block 904).

As further shown in FIG. 9, process 900 may include performing themotion compensation using a second subset of the plurality of samples(block 905).

Although FIG. 9 shows example blocks of process 900, in someimplementations, process 900 may include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 9. Additionally, or alternatively, two or more of theblocks of process 900 may be performed in parallel.

The Techniques for Memory Bandwidth Optimization in Bi-Predicted MotionVector Refinement, described above, can be implemented as computersoftware using computer-readable instructions and physically stored inone or more computer-readable media. For example, FIG. 10 shows acomputer system 1000 suitable for implementing certain embodiments ofthe disclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by computer central processing units (CPUs),Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 10 for computer system 1000 are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system 1000.

Computer system 1000 may include certain human interface input devices.Such a human interface input device may be responsive to input by one ormore human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard 1001, mouse 1002, trackpad 1003, touch screen1010, data-glove 1004, joystick 1005, microphone 1006, scanner 1007,camera 1008.

Computer system 1000 may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen 1010, data-glove 1004, or joystick 1005, but there can alsobe tactile feedback devices that do not serve as input devices), audiooutput devices (such as: speakers 10010, headphones (not depicted)),visual output devices (such as screens 1010 to include CRT screens, LCDscreens, plasma screens, OLED screens, each with or without touch-screeninput capability, each with or without tactile feedback capability—someof which may be capable to output two dimensional visual output or morethan three dimensional output through means such as stereographicoutput; virtual-reality glasses (not depicted), holographic displays andsmoke tanks (not depicted)), and printers (not depicted).

Computer system 1000 can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW1020 with CD/DVD or the like media 1021, thumb-drive 1022, removablehard drive or solid state drive 1023, legacy magnetic media such as tapeand floppy disc (not depicted), specialized ROM/ASIC/PLD based devicessuch as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system 1000 can also include interface to one or morecommunication networks. Networks can for example be wireless, wireline,optical. Networks can further be local, wide-area, metropolitan,vehicular and industrial, real-time, delay-tolerant, and so on. Examplesof networks include local area networks such as Ethernet, wireless LANs,cellular networks to include GSM, 3G, 4G, 5G, LTE and the like, TVwireline or wireless wide area digital networks to include cable TV,satellite TV, and terrestrial broadcast TV, vehicular and industrial toinclude CANBus, and so forth. Certain networks commonly require externalnetwork interface adapters that attached to certain general purpose dataports or peripheral buses (10410) (such as, for example USB ports of thecomputer system 1000; others are commonly integrated into the core ofthe computer system 1000 by attachment to a system bus as describedbelow (for example Ethernet interface into a PC computer system orcellular network interface into a smartphone computer system). Using anyof these networks, computer system 1000 can communicate with otherentities. Such communication can be uni-directional, receive only (forexample, broadcast TV), uni-directional send-only (for example CANbus tocertain CANbus devices), or bi-directional, for example to othercomputer systems using local or wide area digital networks. Certainprotocols and protocol stacks can be used on each of those networks andnetwork interfaces as described above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core 1040 of thecomputer system 1000.

The core 1040 can include one or more Central Processing Units (CPU)1041, Graphics Processing Units (GPU) 1042, specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)1043, hardware accelerators for certain tasks 1044, and so forth. Thesedevices, along with Read-only memory (ROM) 1045, Random-access memory1046, internal mass storage such as internal non-user accessible harddrives, SSDs, and the like 1047, may be connected through a system bus1048. In some computer systems, the system bus 1048 can be accessible inthe form of one or more physical plugs to enable extensions byadditional CPUs, GPU, and the like. The peripheral devices can beattached either directly to the core's system bus 1048, or through aperipheral bus 10410. Architectures for a peripheral bus include PCI,USB, and the like.

CPUs 1041, GPUs 1042, FPGAs 1043, and accelerators 1044 can executecertain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM1045 or RAM 1046. Transitional data can be also be stored in RAM 1046,whereas permanent data can be stored for example, in the internal massstorage 1047. Fast storage and retrieve to any of the memory devices canbe enabled through the use of cache memory, that can be closelyassociated with one or more CPU 1041, GPU 1042, mass storage 1047, ROM1045, RAM 1046, and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As an example and not by way of limitation, the computer system havingarchitecture 1000, and specifically the core 1040 can providefunctionality as a result of processor(s) (including CPUs, GPUs, FPGA,accelerators, and the like) executing software embodied in one or moretangible, computer-readable media. Such computer-readable media can bemedia associated with user-accessible mass storage as introduced above,as well as certain storage of the core 1040 that are of non-transitorynature, such as core-internal mass storage 1047 or ROM 1045. Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core 1040. A computer-readablemedium can include one or more memory devices or chips, according toparticular needs. The software can cause the core 1040 and specificallythe processors therein (including CPU, GPU, FPGA, and the like) toexecute particular processes or particular parts of particular processesdescribed herein, including defining data structures stored in RAM 1046and modifying such data structures according to the processes defined bythe software. In addition or as an alternative, the computer system canprovide functionality as a result of logic hardwired or otherwiseembodied in a circuit (for example: accelerator 1044), which can operatein place of or together with software to execute particular processes orparticular parts of particular processes described herein. Reference tosoftware can encompass logic, and vice versa, where appropriate.Reference to a computer-readable media can encompass a circuit (such asan integrated circuit (IC)) storing software for execution, a circuitembodying logic for execution, or both, where appropriate. The presentdisclosure encompasses any suitable combination of hardware andsoftware.

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

1. A method for encoding of a video sequence in an encoder or decodingof the video sequence in a decoder, comprising: parsing an initialmotion vector from the video sequence associated with a block;determining a plurality of samples to permit both motion vectorrefinement and motion compensation based on parsing the initial motionvector; pre-fetching the plurality of samples; performing the motionvector refinement to determine a final motion vector using a firstsubset of the plurality of samples; and performing the motioncompensation using a second subset of the plurality of samples, whereinthe first subset of the plurality of samples is different than thesecond subset of the plurality of samples.
 2. The method of claim 1,further comprising: determining a maximum distance between the initialmotion vector and the final motion vector; and determining the pluralityof samples based on the maximum distance between the initial motionvector and the final motion vector.
 3. The method of claim 1, furthercomprising: determining a number of taps associated with aninterpolation filter; and determining the plurality of samples based onthe number of taps associated with the interpolation filter.
 4. Themethod of claim 1, further comprising: determining a size of the block;and determining the plurality of samples based on the size of the block.5. The method of claim 1, wherein a maximum distance between the initialmotion vector and the final motion vector, measured in samples, islimited by a video compression technology or standard.
 6. The method ofclaim 5, wherein, in accordance with the video compression technology orstandard, and in association with the video sequence, another block isreconstructed without a motion vector refinement step, and wherein afirst number of taps is used in association with a first interpolationfilter associated with the block, and wherein a second number of taps isused in association with a second interpolation filter associated withthe another block.
 7. The method of claim 6, wherein a sum of the firstnumber of taps and a maximum distance between the initial motion vectorand the final motion vector, measured in samples, is equal to the secondnumber of taps.
 8. The method of claim 6, wherein the first number oftaps is different than the second number of taps.
 9. The method of claim1, wherein a video coding technology or standard prevents the motionvector refinement for at least one pre-determined block size. 10.(canceled)
 11. A device for encoding of a video sequence in an encoderor decoding of the video sequence in a decoder, comprising: at least onememory configured to store program code; and at least one processorconfigured to read the program code and operate as instructed by theprogram code, the program code including: parsing code configured tocause the at least one processor to parse an initial motion vector fromthe video sequence associated with a block; determining code configuredto cause the at least one processor to determine a plurality of samplesto permit both motion vector refinement and motion compensation based onparsing the initial motion vector; pre-fetching code configured to causethe at least one processor to pre-fetch the plurality of samples; firstperforming code configured to cause the at least one processor toperform the motion vector refinement to determine a final motion vectorusing a first subset of the plurality of samples; and second performingcode configured to cause the at least one processor to perform themotion compensation using a second subset of the plurality of samples,wherein the first subset of the plurality of samples is different thanthe second subset of the plurality of samples.
 12. The device of claim11, further comprising: other determining code configured to cause theat least one processor to determine a maximum distance between theinitial motion vector and the final motion vector; and wherein thedetermining code is configured to cause the at least one processor todetermine the plurality of samples based on the maximum distance betweenthe initial motion vector and the final motion vector.
 13. The device ofclaim 11, further comprising: other determining code configured to causethe at least one processor to determine a number of taps associated withan interpolation filter; and wherein the determining code is configuredto cause the at least one processor to determine the plurality ofsamples based on the number of taps associated with the interpolationfilter.
 14. The device of claim 11, further comprising: otherdetermining code configured to cause the at least one processor todetermine a size of the block; and wherein the determining code isconfigured to cause the at least one processor to determine theplurality of samples based on the size of the block.
 15. The device ofclaim 11, wherein a maximum distance between the initial motion vectorand the final motion vector, measured in samples, is limited by a videocompression technology or standard.
 16. The device of claim 15, wherein,in accordance with the video compression technology or standard, and inassociation with the video sequence, another block is reconstructedwithout a motion vector refinement step, and wherein a first number oftaps is used in association with a first interpolation filter associatedwith the block, and wherein a second number of taps is used inassociation with a second interpolation filter associated with theanother block.
 17. The device of claim 16, wherein a sum of the firstnumber of taps and a maximum distance between the initial motion vectorand the final motion vector, measured in samples, is equal to the secondnumber of taps.
 18. The device of claim 16, wherein the first number oftaps is different than the second number of taps.
 19. (canceled)
 20. Anon-transitory computer-readable medium storing instructions, theinstructions comprising: one or more instructions that, when executed byone or more processors of a device, cause the one or more processors to:parse an initial motion vector from a video sequence associated with ablock; determine a plurality of samples to permit both motion vectorrefinement and motion compensation based on parsing the initial motionvector; pre-fetch the plurality of samples; perform the motion vectorrefinement to determine a final motion vector using a first subset ofthe plurality of samples; and perform the motion compensation using asecond subset of the plurality of samples, wherein the first subset ofthe plurality of samples is different than the second subset of theplurality of samples.